Tenant screening method and system using personality assessment

Abstract

A system and method of using a computer and computer program for rapid tenant screening using a personality assessment. The personality assessment measures tenant characteristics then weights those characteristics to predict tenant behaviors of interest to landlords. The tenant is invited to participate in a personality assessment. The computer software and processor generates an assessment report for the landlord indicating the strengths and weaknesses of the tenant's profile. The landlord uses that profile as selection criteria affecting acceptance decision.

What is claimed is: 
     
         1 . A method for evaluating the suitability of a prospective tenant for a rental unit based on results of a personality assessment comprising the use of a computerized selection system comprising computer processors and software programs, wherein said method comprises the steps of:
 a. Identifying said prospective tenant;   b. Providing an Internet portal so that said landlord can access said computerized selection system;   c. Permitting the landlord permission-based access to the computerized selection system through said landlord Internet portal;   d. Sending an invitation to the prospective tenant to participate in said screening method;   e. Providing a prospective tenant access to said Internet portal so that the prospective tenant can access the computerized selection system;   f. Permitting the prospective tenant permission-based access to the computerized selection system;   g. Providing to the prospective tenant a personality assessment comprising a plurality of statements that assess personality traits, attitudes, judgments, and/or candidness of responses on the assessment;   h. The prospective tenant providing responses to said plurality of statements thereby creating a dataset;   i. The computerized selection system using said software programs for scoring said dataset using a proprietary scoring algorithm; and,   j. The computerized selection system generating an assessment report summarizing suitability results about the prospective tenant for the landlord.   
     
     
         2 . The method of  claim 1  wherein the step of permitting the landlord permission-based access to the computerized selection system through the Internet portal comprises the steps of:
 a. The landlord enrolling in the computerized selection system on a subscription or a pay-per-use basis; 
 b. The landlord providing a plurality of suitable identification data to said computerized selection system; 
 c. The landlord choosing an email address and password to access said computerized selection system; and, 
 d. Said computerized selection system establishing an account for the landlord. 
 
     
     
         3 . The method of  claim 1  wherein the step of sending said invitation to the prospective tenant to participate in said screening method comprises the steps of:
 a. The computerized selection system providing a menu of properties under the landlord's administration; 
 b. The landlord identifying a property from said menu of properties in which the prospective tenant wishes to rent; 
 c. The computerized selection system providing a menu of options for ways to invite prospective tenants to complete the personality assessment comprising one of email, mail and telephone; 
 d. The landlord selecting one of said options identified in step (c). 
 
     
     
         4 . The method of  claim 3  wherein the landlord has selected email and wherein the method further comprises the steps of
 a. The landlord inputting the prospective tenant's email address into an appropriate data field; 
 b. The computerized selection system generating an invitation code for use by the prospective tenant; and, 
 c. The computerized selection system sending said invitation code to the prospective tenant's email address. 
 
     
     
         5 . The method of  claim 4  wherein the prospective tenant accesses the Internet portal. 
     
     
         6 . The method of  claim 5  wherein the prospective tenant enters the invitation code into an appropriate data field displayed on the Internet portal permitting the prospective tenant permission-based access to the computerized selection system. 
     
     
         7 . The method of  claim 6  wherein upon entering the invitation code the prospective tenant is provided access to said personality assessment. 
     
     
         8 . The method of  claim 1  wherein the step of scoring the dataset comprises the steps of:
 a. Calculating raw scale scores; 
 b. Combining said raw scale scores to calculate raw sub-behavior scores; 
 c. Combining said raw sub-behavior scores to calculate raw behavior scores; 
 d. Combining said raw behavior scores into an overall acceptance recommendation score; 
 e. Calculating a percentile score for each raw score comprising an overall acceptance recommendation raw score, a behavior raw scores, a sub-behavior raw scores and a scale raw scores; and, 
 f. Displaying a set of requested scores on said assessment report. 
 
     
     
         9 . The method of  claim 8  wherein the step of calculating said raw scale scores comprises the step of the computer software programs producing an average or weighted average of a set of items contributing to a scale responded to by the prospective tenant. 
     
     
         10 . The method of  claim 9  wherein the step of calculating said raw sub-behavior scores comprises the step of the computer software programs combining the raw scale scores with a suitable set of regression weights for optimizing prediction of sub-behaviors for the prospective tenant. 
     
     
         11 . The method of  claim 10  wherein the step of combining the raw sub-behavior scores into said raw behavior scores comprises the following steps:
 a. The landlord selecting and weighting the importance of sub-behaviors; 
 b. The computerized selection system recording said set of importance weights; and, 
 c. The software program calculating a weighted average for each behavior based on said importance weights of the corresponding sub-behaviors that comprise each behavior. 
 
     
     
         12 . The method of  claim 11  wherein the step of combining the raw behavior scores into said overall acceptance recommendation score comprises the following steps:
 a. The landlord selecting and weighting the importance of the behaviors in the overall acceptance recommendation score; 
 b. The computerized selection system recording said set of importance weights; 
 c. The software program calculating a weighted average based on said importance weights of the behaviors. 
 
     
     
         13 . The method of  claim 12  wherein the step of calculating said percentile score for each raw score comprises the computer software executable steps of:
 a. The landlord specifying a comparison sample to be used in comparing scores and generating percentile score information; 
 b. Obtaining the given raw score for the prospective tenant (i.e., the overall acceptance recommendation raw score, behavior raw score, sub-behavior raw score, or scale raw score); 
 c. Calculating a percentile score for the given raw score derived based on comparison of the raw score to said comparison sample; and 
 d. Generating said assessment report in a graphic manner to the landlord. 
 
     
     
         14 . The method of  claim 13  wherein the steps of obtaining said normative percentile score is derived from said comparative sample set chosen by the landlord as an appropriate sample for use in comparing prospective tenants who applied to a given rental unit. 
     
     
         15 . The method of  claim 14  wherein said percentile score describes a percentage of the comparison sample set having a raw score lower than corresponding raw of the prospective tenant. 
     
     
         16 . The method of  claim 15  wherein the step of generating the assessment report includes the step of displaying behaviors and sub-behaviors with a non-zero importance weighting. 
     
     
         17 . A system for evaluating the suitability of a prospective tenant for a rental unit by a landlord comprising:
 a. A computerized selection system comprising:
 i. a computer processing module; 
 ii. a software program module; and, 
 iii. at least one memory module; 
   b. An Internet portal so that said landlord and said prospective tenant can access said computerized selection system;   c. An invitation module for generating an invitation to the prospective tenant to participate in said screening method, said invitation module comprising:
 i. a connection to an email system; 
 ii. a prospective tenant e-mail address; and, 
 iii. a system generated invitation code for use by the prospective tenant for accessing the system. 
   d. A security module permitting the landlord and prospective tenant permission-based access to the computerized selection system, said security module comprising:
 i. a system administrator; 
 ii. a landlord enrollment module; 
 iii. a fee payment module; and, 
 iv. a landlord password management module. 
   e. A personality assessment module comprising a plurality of items associated with a plurality of scales   f. A weighting module whereby the landlord can weight tenant behaviors;   g. A comparison sample module whereby the landlord can define the comparison sample used for calculating percentile scores;   h. A prospective tenant-generated dataset;   i. A dataset scoring module; and,   j. An assessment report generating module for the landlord.   
     
     
         18 . The system of  claim 17  wherein the software program module comprises a scoring key for scoring the dataset wherein said scoring key calculates:
 a. A raw scale score; 
 b. Several raw sub-behavior scores; 
 c. Several raw behavior scores; 
 d. An overall acceptance recommendation raw score; 
 e. A percentile score for each raw score; and, 
 f. Requested scores for display on said assessment report. 
 
     
     
         19 . The system of  claim 18  wherein said raw sub-behavior scores are comprised of weighted raw scale scores using a suitable set of regression weights for optimizing a prediction of behaviors of the prospective tenant.